GRE Subject Test: Psychology : GRE Subject Test: Psychology

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All GRE Subject Test: Psychology Resources

105 Practice Tests Question of the Day Flashcards Learn by Concept

Example Questions

Example Question #201 : Gre Subject Test: Psychology

What is the mode of the following set of scores: 

Possible Answers:

Correct answer:

Explanation:

The mode is the number that occurs most often in the data set. In this case the mode is:

Example Question #202 : Gre Subject Test: Psychology

Which of the following z-scores demonstrates the least significant deviation from the mean?

Possible Answers:

Correct answer:

Explanation:

z-score represents the distance away from the mean for a particular score, expressed in terms of standard deviations. Thus, a z-score of 0 is equal to the mean, and a z-score of 1.4 is equal to 1.4 standard deviations above a given mean.

Example Question #203 : Gre Subject Test: Psychology

A researcher is performing a statistical analysis of data in order to draw conclusions. They are attempting to perform an analysis of variance (ANOVA), but are stymied when all the deviations from the mean sum to zero. The researcher most likely forgot which of the following?

Possible Answers:

Forgot to convert the differences from interval to ratio scale

None of these

Forgot to calculate one average for the negative values and one for the positive values

Forgot to square each difference before summing

Forgot to include adjustments for experimental error (EE)

Correct answer:

Forgot to square each difference before summing

Explanation:

When calculating the sum of squares (SS) as part of an ANOVA, each individual difference from the mean must be squared before summing. This makes intuitive sense when one realizes that the average of all scores which came together to make a mean in the first place must be that mean!

Example Question #204 : Gre Subject Test: Psychology

What is the appropriate inferential statistic to use when your data are from two or more groups of scores, with each score a measure of the same interval/ratio variable, and there are two independent variables and one dependent variable present?

Possible Answers:

Two-factor ANOVA

Multiple regression analysis

T-test

MANOVA

Chi-squared analysis

Correct answer:

Two-factor ANOVA

Explanation:

A two-way analysis of variance is the most appropriate tool for determining simultaneously the effects of two (or more) independent variables on a dependent variable and the strength of the interaction (if any) between the independent variables.

Example Question #205 : Gre Subject Test: Psychology

When conducting a two-way analysis of variance, the degrees of freedom (df) for each factor is best expressed as __________.

Possible Answers:

None of these

one less than the number of trials for that factor

one less than the number of levels for all factors

one less than the number of levels for that factor

one less than the number of participants (n) in each trial

Correct answer:

one less than the number of levels for that factor

Explanation:

The df for each independent variable or factor is determined by how many different levels of that factor are included in the analysis. This can create a problem for calculating sums of squares and ultimately for calculating post hoc analyses, as the number of levels in a factor can be very large.

Example Question #206 : Gre Subject Test: Psychology

Which statistical procedure is best used when there are two or more independent variables, the variables can be held fixed with respect to each other, and a conditional expectation of dependent variable given the independent variables is required?

Possible Answers:

Two-way ANOVA

All of these

Spearman's rank-correlation coefficient

Regression analysis

Analysis of covariance (ANCOVA)

Correct answer:

Regression analysis

Explanation:

A regression analysis, so long as all but one independent variable at a time can be held fixed, is able to produce a predictive window called a conditional expectation that allows for prediction of dependent variable values given set independent variable levels.

Example Question #51 : Other Areas

The primary difference between a sequential sum of squares and an adjusted sum of squares is that the adjusted sum of squares __________.

Possible Answers:

depends on the order in which factors are entered into the model

does not depend on the order in which factors are entered into the model

None of these

only works for models with small values for n

only works for models with large values for n

Correct answer:

does not depend on the order in which factors are entered into the model

Explanation:

An adjusted sum of squares is a model that determines the amount of remaining variance in a model is explained by a factor given that all the other factors are already in the model. For a sequential sum of squares, the amount of variance in a model is explained only given the factors which are already in the model. Thus, the first factor inserted in a sequential sum of squares carries the most weight.

Example Question #52 : Other Areas

All of the following are true about the General Linear Model (GLM) except which of the following?

Possible Answers:

It can test hypotheses using either multivariate or multiple independent univariate tests

It incorporates F-testing, t-testing, linear regression, and ANOVA models

All of these

It generalizes multiple linear regression to more than one dependent variable

It works irrespective of the error terms in each matrix

Correct answer:

It works irrespective of the error terms in each matrix

Explanation:

The general linear model, expressed as , works by comparing a model matrix (sometimes called a design matrix) to a parametric estimate, while also factoring for generalized error terms within the data. It works best when errors are uncorrelated across measurements.

Example Question #207 : Gre Subject Test: Psychology

One appropriate use of a biased ANOVA term for expected mean squares might be which of the following?

Possible Answers:

None of these

If the factors are expected to have an interaction

If the population mean cannot be estimated

If the population means are not equal to one another (the null hypothesis is false)

If one or more terms are nonparametric in the model

Correct answer:

If the population means are not equal to one another (the null hypothesis is false)

Explanation:

A biased EMS is most commonly used when random terms are part of the factors in the model (and thus, when the population means cannot be reasonably assumed to be equal irrespective of treatment effect).

Example Question #27 : Statistical Procedures

All of the following are true about Pearson's r except which of the following?

Possible Answers:

Sample r is extremely accurate at estimating population correlation coefficients if sample size is large

All of these

Confidence intervals cannot be established for weak values of r

Strength of correlation ranges from -1 to 1

Sampling distribution can be made to fit Student's t-distribution

Correct answer:

Confidence intervals cannot be established for weak values of r

Explanation:

Constructing a confidence interval for Pearson's r can be done through a process called "bootstrapping", which involves re-sampling with replacement a certain number of values in each correlation a large number of times.

All GRE Subject Test: Psychology Resources

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